Assistive Intelligence Labs

Our Methodological Universe

Our methodology merges critical disability scholarship with computational innovation. We operate through five interconnected pillars that guide every aspect of our research, design, and engineering practice.

Our Five Methodological Pillars

Posthuman Speculative Design

Assistive technologies are conceptualized beyond human–machine binaries—our systems extend perception (acoustic sensing), cognition (reasoning LLMs), mobility (autonomous wheelchairs), and communication (neuro-symbolic sign-language models) into hybrid intelligences.

  • Extended Perception

    Acoustic sensing systems that create new sensory modalities

  • Augmented Cognition

    Reasoning LLMs that enhance decision-making and understanding

  • Enhanced Mobility

    Autonomous wheelchairs creating new forms of movement agency

  • Hybrid Communication

    Neuro-symbolic sign-language models bridging linguistic divides

Social Model + Crip Technoscience

We design systems that dismantle infrastructural and epistemic barriers—not technologies that medicalize disability or reinforce deficit-based narratives. Our approach centers on removing barriers rather than "fixing" bodies.

Core Principle: Impairment does not disable; exclusionary infrastructures do. We build technologies that challenge and transform the environments that create disability.

Decolonial AI Futures

Every dataset, every device, every model is created locally: no imported corpora, no opaque foreign APIs, and no extractive data practices.

We build sovereign AI infrastructures that encode:

  • Indigenous signing practices
  • Local mobility realities
  • Cultural sensory cues
  • Contextual healthcare behaviors
  • Spatial–acoustic signatures of Ugandan environments

Our commitment to AI sovereignty ensures that African disability knowledge systems remain under community control, free from colonial extraction and corporate surveillance.

Neuro-Symbolic & Sensorial Computation

Our systems integrate multimodal pipelines that combine neural learning with symbolic reasoning and embodied sensing:

Large Vision Models (LVMs)

Gesture interpretation and visual understanding systems

Graph Reasoning Engines

Disability-specific knowledge representation and inference

Federated Learning

Privacy-preserving model adaptation across communities

IoT–Robotics Fusion

Autonomous movement and environmental interaction

Spatial Acoustics + NLP

Auditory scene understanding and interpretation

Co-Creation & Participatory Engineering

PWDs are not recipients—they are design authorities, shaping algorithmic behaviors, data taxonomies, interface requirements, and ethics.

Community Leadership

PWDs lead every stage of the design process, from conceptualization to deployment

Algorithmic Shaping

Communities define how AI systems behave and make decisions

Data Taxonomies

Local knowledge systems inform how data is organized and understood

Interface Design

User requirements emerge from lived disability experiences

Ethical Frameworks

Community values guide technology development and deployment

What We Are

Research Lab

Advancing critical disability scholarship through computational methods

Maker Space

Building tangible technologies with communities and craftspeople

Policy Engine

Shaping regulations and frameworks for inclusive digital futures

Imagination Workshop

Designing technologies that anticipate not just tomorrow, but multiple futures

Explore Our Technologies

See how these methodological principles manifest in our intelligent systems and assistive technologies.

Sign Language AI Mobility Systems Sensory Interfaces